跟读练习: Will YouTube Ever Run Out Of Video IDs? - 通过视频学习英语口语
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1
Every YouTube video has a unique ID.
2
It's up there in the URL, a string of 11 characters that uniquely identifies which video you want.
它就在网址里，是一串由11个字符组成的字符串，可以唯一标识你想要的视频。
3
Now, YouTube has millions and millions of videos.
4
The last stats that they released said that they have 400 hours of video being uploaded every minute.
他们公布的最新数据显示，每分钟有400小时时长的视频被上传到平台。
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So, are they ever going to run out of those IDs?
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Well, to find out, let's talk about counting systems.
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People count in base ten.
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Zero to nine.
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That'll be, hopefully, familiar to you.
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Computers count in base two, in binary.
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But that's difficult for humans to read.
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It gets too long to write really, really quickly.
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So, often computers will display it in base sixteen.
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Hexadecimal.
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You have zero to nine, and then A to F, and then you start adding to the next column.
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Humans can't understand that easily, but it's efficient if we have to type it in somewhere.
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And sixteen, two to the power of four, is also easy for computers to deal with.
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So how about base 64?
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That'd be a ridiculous counting system, right?
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Except 64 is another one of those easy numbers for computers.
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It is 2 to the power of 6.
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And humans can get to 64 very easily.
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0 to 9, then capital letters A to Z, then small letters A to Z, and two other characters.
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Most Base64 uses slash and plus, but they don't work so well in URLs, so YouTube uses hyphen and underscore.
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That YouTube URL, that unique ID, is really just a random number in Base64.
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They could have picked Base10 or Base16, but they didn't.
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They went with 64, because it will let you cram a huge number into a small space
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and still make it vaguely human-readable.
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Author and programmer Sam Hughes, by the way, pushed this to the limit and invented base 65,536,
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which includes basically every character from every language.
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It is ridiculous and unnecessary, but when has that ever stopped programmers?
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So, why didn't YouTube just start counting at one and work up?
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Well, first, they would have to synchronise their counting between all the servers handling the video uploads.
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Or they'd have to assign each server a block of numbers.
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Either way, there's a lot of tracking to do, a lot of making sure that it's never duplicated.
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Instead, they just generate a random number for each video, see if it's already taken, and if not, use it.
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And secondly, it is a really, really bad idea to just count one, two, three, or so on in URLs.
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Incremental counters, as they're called, can be a big security flaw.
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If you see video 283 up there, then you might wonder, what's video 284?
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Or video 282?
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It's easy to enumerate, as it's called, to run through the entire list.
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YouTube unlisted videos, the ones that don't appear publicly, but that you can send a link to people, those wouldn't work.
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And by the way, lots of badly designed sites do use incremental counters and it is a terrible idea.
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It might tell your competitors exactly how many customers you have, because they can just count them.
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It might let people download all your records easily, because they can just run through them.
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And in one site that someone in Florida emailed me about this week, it lets you look at other people's personal details.
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Don't use incremental counters.
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If you're building a website, use a random number.
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Which brings me to the question, just how big are the numbers that YouTube uses?
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Well, let's work it out.
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One character of base 64 lets you have 64 ID numbers.
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Two characters, that is 64 by 64, or 4096.
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Three characters, 64 times 64 times 64, or 64 to the power of 3, that is already more than a quarter of a million.
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And if we go to four, well, now we're above 16 million.
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If you used base 64, then you can assign an ID number to everyone who lives in London down there twice over,
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and you'll only need four characters.
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This gets big fast.
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We can keep on doing this, and by seven characters, we are already at four quadrillion.
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Now I assume that YouTube checks through a dictionary and doesn't allow any actual words to appear up there,
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particularly anything rude, but that is going to be a tiny minority of their URLs, so for our purposes, we can pretty much just ignore that.
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At YouTube's 11 characters, we are at 73 quintillion 786 quadrillion 976 trillion 294 billion 838 million 206 thousand and 464 videos.
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That is enough for every single human on planet Earth to upload a video every minute for around 18,000 years.
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YouTube planned ahead.
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Can they run out of URLs?
65
Technically, yes.
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Practically, no. And if they did, they could just add one more character.
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Oh, one take!
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One take!
69
Yes!
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谁适合看这个视频？
这个视频适合有一定英语基础、想通过趣味内容提升听力和词汇的学习者。它用通俗易懂的语言解释技术问题，语速适中，适合用来练习“看视频学英语”和“英语影子跟读”。无论是想积累科技类表达，还是锻炼理解长段落的能力，都能从中受益。
值得借鉴的词汇和习语
- enumerate：逐一列举。例：It's easy to enumerate（很容易逐一查看）。
- incremental counters：递增计数器。文中指按1、2、3顺序编号的方式。
- cram a huge number into a small space：把大量数字压缩进小空间。形容Base64编码的高效。
- quadrillion：千万亿（10的15次方），quintillion：百万亿亿（10的18次方）。这些大数表达在科技讨论中很实用。
如何练好发音？
这个视频的 speaker 发音清晰，语速平稳，非常适合“shadow speech”练习。以下是重点：
- 注意数字表达的连读，比如“64 quadrillion”中“64”和“quadrillion”的自然衔接。
- 模仿重音位置，如“uniquely identifies”“ridiculous and unnecessary”，通过重音突出关键信息。
- 练习长句断句，比如“that's enough for every single human... 18,000 years”，跟着视频停顿，提升口语流畅度。
想要快速进步？可以用“shadowing site”反复跟读，对比自己和 speaker 的发音差异。坚持练习，不仅能提高英语发音，还能掌握科技类话题的表达逻辑。
视频里提到YouTube的ID设计几乎不会用完，是不是很有趣？边学英语边涨知识，这样的“看视频学英语”方式你喜欢吗？
什么是跟读法？
跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。